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dc.contributor.authorZou, Yong
dc.contributor.authorZheng, Chao
dc.date.accessioned2022-05-12T19:36:24Z
dc.date.available2022-05-12T19:36:24Z
dc.date.issued2022-04-25
dc.identifierdoi: 10.3390/app12094333
dc.identifier.citationApplied Sciences 12 (9): 4333 (2022)
dc.identifier.urihttps://hdl.handle.net/20.500.12588/856
dc.description.abstractThe effects of a landslide can represent a very big problem, including the death of people, damage to the land, environmental pollution and the loss of natural resources. Landslides are the most important medium for transferring sediments and polluting waterways by earth and organic materials. An excess of sediments reduces the quality of fish habitat and the potability of water. In order to understand landslides in depth, a thorough study was conducted using a scientometric analysis, as well as a thorough practical examination of landslide analysis and monitoring techniques. This review focused on methods used for landslide analysis, including physical models requiring easily prepared event-based landslide inventory, probabilistic methods which are useful for both shallow and earthquake-based landslides, and landslide monitoring performed by remote sensing techniques, which provide data helpful for prediction, monitoring and mapping. The fundamental principles of each method are described in terms of the method used, and its advantages, and limits. People and infrastructure are at danger from landslides caused by heavy rain, so this report highlights landslide-prone regions and considers the analysis methods for landslides used in these countries, with a view to identifying mitigation measures for coping with landslide risks in hilly areas. Furthermore, future landslide research possibilities, as well as possible modeling methods, are addressed. The report summarizes some landslide prediction and monitoring techniques used in landslide-prone countries which can help inform researchers seeking to protect the public from danger in landslide areas.
dc.titleA Scientometric Analysis of Predicting Methods for Identifying the Environmental Risks Caused by Landslides
dc.date.updated2022-05-12T19:36:27Z
dc.description.departmentCivil and Environmental Engineering


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